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Learning Geospatial Analysis with Python-Second Edition

You're reading from   Learning Geospatial Analysis with Python-Second Edition An effective guide to geographic information systems and remote sensing analysis using Python 3

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Product type Paperback
Published in Dec 2015
Publisher Packt
ISBN-13 9781783552429
Length 394 pages
Edition 1st Edition
Languages
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Author (1):
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Joel Lawhead Joel Lawhead
Author Profile Icon Joel Lawhead
Joel Lawhead
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Table of Contents (12) Chapters Close

Preface 1. Learning Geospatial Analysis with Python FREE CHAPTER 2. Geospatial Data 3. The Geospatial Technology Landscape 4. Geospatial Python Toolbox 5. Python and Geographic Information Systems 6. Python and Remote Sensing 7. Python and Elevation Data 8. Advanced Geospatial Python Modeling 9. Real-Time Data 10. Putting It All Together Index

Routing along streets


Routing along streets uses a connected network of lines called a graph. The lines in the graph can have impedance values that discourage a routing algorithm from including them in a route. Examples of impedance values often include traffic volume, speed limit, or even distance. A key requirement for a routing graph is that all of the lines, known as edges, must be connected. Road datasets created for mapping will often have lines whose nodes do not intersect. In this example, we'll calculate the shortest route through a graph by distance. We'll use a start and end point which are not nodes in the graph, which means we'll have to first find the graph nodes closest to our start and destination.

To calculate the shortest route, we'll use a powerful pure Python graph library called NetworkX (NX). NX is a general network graphing library which can create, manipulate, and analyze complex networks including geospatial networks. If pip does not install NetworkX on your system...

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